Leonie Monigatti

This talk explores agentic search as a critical component of context engineering for Large Language Models (LLMs). The core thesis is that effective context curation for LLMs relies heavily on sophisticated search mechanisms, moving beyond simple retrieval to agent-driven exploration of diverse information sources. The presentation highlights the evolution from basic RAG to agentic RAG and emphasizes the challenges and strategies for building robust search tools that agents can effectively utilize.